Vehicle Control System for Collision Risk Minimization
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Solution Overview
Problem
Current vehicle control systems rely on multiple independent modules that struggle to provide a holistic assessment of the environment, leading to suboptimal decision-making and loss of information during transitions between modules, resulting in inefficient navigation and increased collision risks.
Innovation Solution
A method that determines driving risks across multiple positions and times to calculate a trajectory that minimizes overall risk, incorporating driving dynamics and comfort parameters, allowing for continuous optimization and prediction of future scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple independent control modules are used to handle different driving situations, then the system can cover more specific scenarios, but the device complexity increases and information loss occurs during module transitions
Solution Approach 1:
The patent merges multiple independent control modules into a single integrated control unit that processes all driving situations through unified machine learning models. This consolidation eliminates the need for switching between multiple specialized modules, reducing system complexity while maintaining comprehensive scenario coverage through universal deep learning architectures.
Solution Approach 2:
The patent implements a universal control module capable of handling diverse driving scenarios through multi-functional machine learning models. The single control unit can adapt to various situations (lane changing, intersection navigation, obstacle avoidance) by processing sensor data through versatile neural networks, eliminating the need for separate specialized modules for each scenario.
2Adaptability or versatility
If multiple independent control modules are used, then specific behavior patterns can be triggered for different situations, but information loss occurs when switching between modules
Solution Approach 1:
The patent ensures continuous environmental assessment and trajectory optimization by maintaining uninterrupted sensor data processing and model updates. The unified control unit continuously refines the driving trajectory based on real-time sensor inputs without interruption from module switching, preserving all environmental information throughout the decision-making process.
Solution Approach 2:
The patent performs preliminary environmental assessment and risk calculation for all possible trajectories before final decision-making. By pre-processing sensor data and evaluating multiple potential paths in advance, the system maintains complete environmental awareness and prepares comprehensive information for the optimal trajectory selection, eliminating information loss during transitions.
3Reliability
If a holistic assessment of the environment is performed to determine optimal trajectories, then collision risks are reduced, but the computational complexity and time required for decision-making increase
Solution Approach 1:
The patent performs preliminary calculation of risk values for multiple potential trajectories in advance, before the vehicle reaches critical decision points. By pre-evaluating collision risks, energy consumption, and trajectory feasibility for all possible paths, the system prepares optimized solutions ahead of time, enabling rapid final decisions without intensive real-time computation during critical moments.
Solution Approach 2:
The patent implements dynamic trajectory optimization that adapts the level of computational detail based on the driving situation. For routine scenarios, the system uses pre-computed trajectories with minor adjustments, while for complex situations, it performs more intensive real-time optimization. This dynamic approach balances comprehensive safety assessment with computational efficiency and real-time responsiveness.
Data Source
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Figure 3A
AI summary
A method for steering a vehicle from its current position to the vicinity of a target position comprises determining (S102) the driving risk of a plurality of positions in the vicinity of the vehicle at a current time and at several times following the current time, and determining a trajectory for the vehicle that connects or approximately connects the current position and the target position, taking into account calculated driving risks (e.g., based on collision probabilities, traffic rules) as well as vehicle dynamics and comfort parameters. The vehicle is then steered along the modified trajectory (S110).